Reasons to Rock the Boat

After spending time at Amazon and Meta (formerly Facebook), Stephen Newton knows what a visionary leader looks like. Jeff Bezos and Mark Zuckerberg certainly fit the bill. Now, Newton is looking to back the next generation of these leaders at his technology-focused investment firm Occipital Ventures. On this episode of the Voices of Experience podcast, Newton shares how he helped Amazon and Facebook stay in compliance with data protection and privacy laws, and out of the news. We also talked about what makes a visionary leader, the future of AI in business and why you should rock the boat at your job.

Show Notes

Daniels alumnus Stephen Newton is the founder and CEO of technology investment firm Occipital Ventures. His previous experience includes compliance manager for Kindle, head of trust and science for Alexa and director of new legal obligations at Meta.

1:12 Making an impact at a big company
5:08 Staying in compliance and out of the news
7:45 Trust and science in tech
8:38 Switching to the investor side of the table
Investing in the visionary and what defines one
14:04 Why AI is crucial to Stephen’s investments and personal life
16:58 Using AI for good
20:35 “Rock the boat”
24:02 Show notes and credits

In this episode:

Stephen Newton’s LinkedIn
Check out Newton’s AI collection
FACT SHEET: President Biden Issues Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence
Upcoming workshops from Entrepreneurship@DU

Online extra: Are you more interested in investing in great leaders or great ideas?

VOE Podcast · Are you more interested in investing in great leaders or great ideas?

Transcript

Nick Greenhalgh

Today, on the Voices of Experience Podcast. How critical is integrating artificial intelligence into your business?

Stephen Newton

If a new company isn’t utilizing AI to gain acceleration, they will probably not win in their space.

Nick Greenhalgh

That’s Stephen Newton, a Daniels alumnus and the boss at tech investment firm Occipital Ventures. AI is clearly an important element in his business strategy, but we learned that it also has a role in Newton’s personal life too.

Stephen Newton

“And so we went back to my house and we sat down and I said, Hey, do you want to see my AI collection?”

Nick Greenhalgh

Stay tuned for that story’s payoff later in the episode, I promise it’s worth it. But first, Newton joined the show to share the lessons he learned in previous stops in his career. Most notably, as head of trust and science at Amazon’s Alexa and Director of New Legal Obligations at Facebook. We also talked about what makes a visionary leader and why you should rock the boat at your job. Stephen, welcome to the show!

Stephen Newton:

Thank you. Happy to be here.

Nick Greenhalgh:

I want to start with your career in two interesting stops that you’re recently at. So in that career you’ve worked at two of the 10 most valuable companies in the world, Meta formerly Facebook and Amazon in roles varying from compliance manager for Kindle, head of Trust and science for Alexa and director of new legal obligations at Meta. How do you find your way and make an impact at huge companies like that?

Stephen Newton:

It’s a great question. Well, when I started at Amazon, it wasn’t one of the top companies in the world. It was big, but it wasn’t nearly what it is today. It grew, I think by market cap from 50 billion to 500 billion while I was there. So opportunities come up. I mean, in a company that’s growing that quickly, there are endless problems to solve. And if you are good at finding problems that can accelerate the company, solving them in elegant ways and building automation to sort of continue that process going and in a way that can scale, you can really sort of make your mark. So I wouldn’t say that I did anything special. I think I was lucky that I ended up at this company who was going through this explosive growth period and had a bunch of really crazy challenges that I needed to figure out how to solve.

Meta was the opposite. In fact, it wasn’t called Meta when I was there. It was called Facebook. It transitioned while I was there to meta and they were trying to reinvent themselves after a few issues, public issues that everyone read about and what was once a very beloved company had to sort of reimagine itself to get trust back in the community. And it was a lot different. It is still a growing company. It’s still a big explosive tech company, but users of the Facebook app were declining, which that hadn’t happened before. So totally different experiences, different life cycles of the businesses, but both extremely exciting, interesting opportunities.

Nick Greenhalgh:

Great. You mentioned the pace of how quickly things move at those companies. How do you keep up?

Stephen Newton:

Well, when I left Amazon after 10 ish years, including some consulting work on the front end, I equated my time at Amazon to dog years. So it wasn’t 10 years, it was like 70 years. It really moves very fast. But for someone like me, that’s exciting. I like the speed, I like the pace. It provides tons of challenges, tons of opportunities. There were days you would be in the office for a long time, but it forced you to think about problems in very different ways.

For instance, if you’re growing at 10% a year, that’s pretty manageable. You hire, you build systems, you can manage 10% growth, but when your business is growing at a thousand percent a year, you can’t just throw people at it. It will break. And so it forces you to think about problems from a tech perspective, from this crazy growth perspective. And you utilize things you would never think about. You build systems, you don’t buy systems off the shelf. You build something special that will work for this growth for this business, and then you turn it into a product. So it’s a flywheel, right? It’s a flywheel effect. You build a system to sustain your growth and manage a business, and then you can sell it to another company outside the company. And so you get two for one. And I don’t know if there are very many companies out there that can do it like Amazon does.

Nick Greenhalgh:

Yeah. I also mentioned in my intro there your titles, and I think the one that I liked particularly the most was the head of trust, head of trust in science for Alexa. With so many eyes on these large technology companies, how did you ensure your divisions, the things that you managed, remained in compliance and out of the news?

Stephen Newton:

It’s a great question, and really the way to do it is to think about the product from the customer’s perspective. What experience do they expect? And the goal is to not give them something they don’t expect. And it’s really hard to do that. Alexa is a complex business. It’s AI. You often get responses or interactions with the device that you don’t expect, whether it’s because of the product itself that Amazon controls on its side, or if it’s your internet being laggy that day, or if someone’s talking in the background or if the phone rings while you’re trying to say a command. We’ve all had these experiences.

So customers can be pretty forgiving on those types of things, but they’re not forgiving if the product simply does something unexpected, especially if it’s a bad experience. So in order to create good experiences, I mean, that’s the core idea. So you get really good at the things that people use it the most for, and then you sort of work around the edges and get the long tail of all the other experiences that people are using.

But the hardest challenge with Alexa is that we didn’t control the hardware on every product. So they’re the Amazon branded products. So those are the Echo devices, and then there’s Bose and Sonos and a myriad of other products, and you don’t control the hardware on those products. So while Sonos might use a very sophisticated mic setup that really captures your voice well, and therefore the Alexa toolkit on the backside can understand what you’re saying and process it. Some of the products, they’re budget products and they have a two mic array instead of a three or four mic array, and it doesn’t pick up your voice as well, and now you get a bad experience. So how do we control sort of the software product that we control and then the hardware products that exist in the marketplace, and creating a balance so that you can help your product proliferate without giving it those hindrances where people will be less likely to keep enjoying the product is the hard part.

Nick Greenhalgh:

And how does the interplay of trust and science work together?

Stephen Newton:

So science is just a fancy name for business intelligence and trust is a fancy name for not harming people, I would say.

Nick Greenhalgh:

Got it.

Stephen Newton:

So what we did is we created these really sophisticated business intelligence toolkits to analyze when products were doing things that they shouldn’t. And it’s not always a harmful impact, it’s just we see delay, we see an experience that we wouldn’t expect, or sometimes we’ll poll the user and say, is this what you expected? And they’ll say no. So we’ll get signal that that’s something we should look at.

There’s also other things that people don’t really think about. So there’s a certain amount of server capacity for the product. And so every Alexa impacts how much server capacity there is. Well, if everyone on the East Coast sets their alarm for 6:00 AM via Alexa, there’s a lot of pressure on the server at that time. And what happens if there’s no server capacity to manage that interaction? Well, it doesn’t happen. So now somebody doesn’t wake up at 6:00 AM for their work and then they’re late. We have to do things like, okay, we’ll have flexible server capacity. We know that these are peak times. These are things that you just do, but for any software product, but for Alexa, because it’s so personal and intimate with voice and microphones in your home, you can’t mess it up.

Nick Greenhalgh:

We’ll come back to Meta and Amazon and Alexa and those things in a little bit, but I want to talk about the next part of your career. So after your time in the technology space, you transitioned to the other side of the table as an investor. How different is it to be the one writing the checks?

Stephen Newton:

I would say that I learned a lot at Amazon and a lot at Meta. Amazon kind of runs like a bunch of mini startups. Every business in Amazon is compartmentalized to a degree and they run their own P&L, and the businesses can be relatively small. Meta on the other hand is the opposite. It’s massive and it spins off 30% profit a year and only sort of now. And while I was there were they sort of thinking differently about expense.

But when you work with a startup, money is everything, right? It’s the lifeline. Without money, there’s no runway. You can’t make it to a mature product or a mature business. And teaching young entrepreneurs how to manage the cashflow is really hard because a lot of people who start businesses have great ideas, but they’re not necessarily great business people. They’re engineers, they understand a space, they’re a subject matter expert in a particular area, but they’ve never managed a P&L. And so teaching them the value of every dollar and teaching them how to spend it wisely so they get that runway can be hard.

Nick Greenhalgh:

In speaking of leadership, you worked for years under Jeff Bezos and Mark Zuckerberg. I think it’s probably fair to call them both visionaries, right? Did experiences under those leaders motivate Occipital Ventures tagline of investing in the visionary?

Stephen Newton:

Absolutely. I feel like every visionary is initially thought of as sort of a lunatic, and maybe they are. Honestly, some of the things that these businesses are doing are science fiction to a pretty wild degree. So I think that’s definitely true.

I would say though that they weren’t necessarily my inspiration for the tagline. It goes back to what I was saying earlier. I think the visionaries I’m looking for are people who have deep, deep subject matter expertise in a particular area. And so that actually ironically wasn’t Mark Zuckerberg or Jeff Bezos, they sort of saw an opportunity in the business place and said, oh, I can build something here. They didn’t necessarily have experience selling books online or social media, which didn’t really exist outside of MySpace at the time. The opposite is really true for what we look for. We’re looking for people who they’ve been in this particular niche business for 30 years, and it’s never really had an entrepreneurial spirit, a tech backbone, and now they can come in and say, Hey, we can optimize this. We can use technology to accelerate this industry in a way that it’s never been done before. And so maybe visionary isn’t the right word. It’s deep subject matter experts, kind of like old school people in the business who see a better way to do it.

Nick Greenhalgh:

I’m going to keep using the term visionary because I like it for the purpose of this, but you mentioned a few things there, but what attributes in your mind define someone who you’d call a visionary?

Stephen Newton:

So for me it’s curiosity. I think the hardest part for business people who’ve been doing what they’ve been doing for a really long time is thinking differently than what’s worked for them in the past. And that’s why you see legacy businesses fall off, they get into a mode of doing business and they continue doing it as long as possible, and they have trouble inventing new ways to do it. So when I see somebody who has deep subject matter expertise but is also curious about things that are coming up, I get really excited.

Nick Greenhalgh:

And are people born a visionary or can you grow into one?

Stephen Newton:

That’s a good question. I will say I don’t know the answer to that to be honest. I think everyone’s different. I think some people can and some people can’t. But what I will say is that when you show somebody a piece of technology for the first time, you can tell if their eyes light up and they start to connect the dots and say, oh my gosh, if this technology were applied to this problem or that problem, or whatever they’re an expert in, then you know if they have that capability, or some people say, I don’t get it, or that’s interesting, but they don’t start to think about it from their worldview. And I think AI is a good example of that. When you talk to people about AI, it seems farfetched, it seems sci-fi, but when you show somebody the power of AI in real time, it’s a pretty transformative thing. And people will all of a sudden start to think about the problems that they work on in their business or their life through the lens of this new tool, and you can see this change happen in them.

Nick Greenhalgh:

Yeah. I want to skip ahead here because you mentioned AI, and I know that’s something that’s very important to you when you’re looking at investing in companies. I think I’m setting this up correctly, but what are the key indicators you’re looking for in an investible company?

Stephen Newton:

As far as AI goes, AI. And I think it’s hard because not everyone has this exposure to AI yet, but it’s starting to proliferate in a way as a consumer product that everyone can get their eyes on it and understand the impact that it has. If a new company isn’t utilizing AI to gain acceleration, they will probably not win in their space. If a company has a plan to use AI or hasn’t thought about AI yet, I would probably not invest in the company because it needs to be part of the strategy from the beginning, because otherwise the solution is decision tree algorithms or hiring people, which is not efficient. And cashflow is king, particularly in a resource constrained environment like we’re in today.

Nick Greenhalgh:

And AI is clearly very important to you and a key pillar of your own interest, so much so that you used it as a pickup line for your wife, is that right?

Stephen Newton:

I wouldn’t say a pickup line. I would say I’m just a nerd, and I was really excited to share AI with her.

Nick Greenhalgh:

Tell our listeners that story.

Stephen Newton:

So the first date my wife and I went on, we were introduced by a very good friend at Microsoft, and he thought we would be a good match, and we met, we went on a date and we shut the restaurant down. We sat there for four hours, and before we knew it, the waiter was asking us to leave because they wanted to go home. And so we went back to my house and we sat down and I said, Hey, do you want to see my AI collection?

Nick Greenhalgh:

Naturally.

Stephen Newton:

Naturally for me, I think most people on earth would flee for the hills, but fortunately, she stuck around and she was interested. I mean, she’s a technologist. She works in tech as well, and even though she doesn’t get as excited about AI from an entertainment perspective as I do, she understands the power and utilizes it for work as well. So match made in heaven all centered around AI.

Nick Greenhalgh:

So I know what a record collection or a book collection might look like. What is an AI collection?

Stephen Newton:

It’s a book collection.

Nick Greenhalgh:

Okay.

Stephen Newton:

There’s some pretty exciting authors out there writing some good stuff. But the other part of that story is I sat her down and I said, Hey, we should watch this movie. You’ll love it. And I don’t know if you’ve heard of Ex Machina.

Nick Greenhalgh:

Yeah.

Stephen Newton:

But it’s about the most boring date movie you could possibly imagine. But I love it. It’s a great AI movie, and so we watched about half of it before she had had enough, and so I took her home and she still went on a second date with me. So it worked out, but I wouldn’t suggest this for anyone looking to woo a nice lady.

Nick Greenhalgh:

The president recently released an executive order on safe, secure, and trustworthy artificial intelligence, laying out a few critical standards for safety moving forward. How should companies ensure that AI is used for good?

Stephen Newton:

It’s a great question. I don’t think any company builds products thinking we’re going to use this for evil. I think the intent is always good, and I think Facebook is probably the prime example of this. Facebook was designed and beloved for years, and I think people forget that time, honestly. But it was exciting when you met somebody and you added them on Facebook and you saw how many mutual connections you had. It was this really interesting new thing. It wasn’t until a decade or so had passed that people started to recognize some of the harms that it was causing and some of the damage it was doing to society and politics and just lots of abuse and things like that.

So I always encourage business leaders and technologists to try to look around corners to say, okay, how can we predict what downside impacts this product may have? And how can we control for the harm it may cause? I think it’s impossible to prevent all harm. I think you can do your best to get to 99.9% or better, and I think that should be the goal, but you should always be trying to predict bad outcomes of your products and what they may cause.

Nick Greenhalgh:

So it’s important to look at that net positive benefit of AI?

Stephen Newton:

I think so. But again, right, if it’s still causing lots of harm and deaths, we should always work to fix that, but I don’t think we should throw a tool like this out if it does cause some harm. I think the goal is to always reduce harm to zero, but we need to understand that there’s a maturation process to get there.

Nick Greenhalgh:

Great. For aspiring business leaders, maybe current students or recent graduates looking to get a leg up as it comes to AI, how do you recommend they start? Where should they look? What should they know?

Stephen Newton:

Well, when I was at Daniels, Daniels sort of prided itself on saying that every student that comes through Daniels knows Excel. Well, I think every student that gets through Daniels should know AI, and I don’t mean AI from a coding perspective, from a deep technological perspective, but at least know how to use it to solve problems or accelerate yourself. I think AI is useful for a ton of stuff, but one of the things that it’s most useful for is for saving time. And so as a business leader, you can do more and be more efficient if you know how to use AI to get you there.

Nick Greenhalgh:

And does that manifest itself in prompting AI, knowing the right questions to ask? How does that look like on a practical sense?

Stephen Newton:

Yeah, in large part, it’s like any algorithm garbage in and garbage out. So knowing what to ask, how to ask it to get to the right outcome is key. But more importantly, from a business perspective, if you’re a business leader, you see a problem in the business space and you can think, okay, I can throw people at this problem. I can throw a process at this problem, or I can use an elegant AI solution to do repetitive work in a way that doesn’t require a ton of investment on people or systems.

Nick Greenhalgh:

You mentioned your time at Daniels, and I want to talk about that. You graduated with an accounting and finance degree in what you called a speed run, completing the degree in two years rather than four. In that short time, how did the college’s ethics-based education impact your own career aspirations?

Stephen Newton:

It impacted my career far more than I would’ve expected. I had no intention of being in compliance. I had no intention of doing ethics as a job. Frankly, most people don’t understand that it is part of the business world in a very formal sense, but it worked out that way because Daniel’s taught me to think a little bit differently about business problems.

I think that when most people think about business ethics, they think there’s this good and evil paradigm. Everything is black and white, but that’s simply not the case. If you’re sitting in a business room and there’s really smart people around you and somebody suggests, Hey, we should sacrifice customer safety for profits, that’s an easy problem to solve. But it’s never like that. For instance, when you’re at Meta and they’re talking about hate speech or censorship, it’s like from a business perspective, censoring people isn’t good. People don’t like when they can’t express their opinion. You lose customers. But from a business perspective, how do you think about the long-term impact of the business if you allow people to say things that maybe drive other people away? So it’s very hard. It’s not black and white.

In my experience Daniels really gave me a leg up on thinking about these problems differently as well as Notre Dame, Notre Dame did the same thing. But I think the biggest challenge is speaking out when you’re in a room of really smart people, particularly people who may be more senior than you, and they have an opinion, it’s really hard to say, I don’t agree, because your career is on the line, right? You’re trying to get ahead. It’s hard to make waves, but in some cases, we need to do that. And I think, I hope students from Daniels take their ethics education and they go out there and do that, and they rock the boat and they challenge things that they don’t think are right.

Nick Greenhalgh:

So I want to get to our last question here. One that we ask all of our guests. As a voice of experience what is one thing you’d like to share with our listeners?

Stephen Newton:

I think it’s most important to figure out how to solve complex problems in elegant ways. And if you can figure out ways to do that in really whatever business you’re in or relationships you can really succeed. I think the challenge is when people get into linear thinking and they can’t escape what has worked or what they’re used to doing that they get stuck. But I think there’s this endless opportunity for growth, and I think AI is a great example of that, where if you can keep learning and keep trying new ways of solving problems, you can accelerate your career and you can go as far as you want. You can build the next satellite cluster or colony on Mars, but you have to be willing to really think outside the box.

Nick Greenhalgh:

Great. Thank you, Stephen. We really appreciate it.

Stephen Newton:

Absolutely. Thank you.

Nick Greenhalgh

If you want to see what’s in Stephen’s AI book collection, be sure to head to our show notes. And if you’re looking for ways to become a little more fluent in AI, we’ll link to some upcoming workshops from Entrepreneurship@DU. We’ll also have a bonus question there for Stephen on if he’d rather invest in a great idea or a great leader. You can find those show notes and past episodes at daniels.du.edu/voe-podcast. The VOE Podcast is an extension of Voices of Experience, the signature speaker series at the Daniels College of Business, sponsored by U.S. Bank. Sophia Holt is our sound engineer. Joshua Muetzel wrote our theme. I’m Nick Greenhalgh and we’ll talk again soon.

Show Notes

Table of Contents

In this episode:

Related articles and information:

Online extra: Are you more interested in investing in great leaders or great ideas?

Transcript

Submit a Comment Cancel reply

DANIELS COLLEGE OF BUSINESS AT UNIVERSITY OF DENVER